人脸表情识别的Gabor变换最优通道模糊融合方法

A fuzzy fusion approach to gabor transform optimal channels for facial expression recognition

根据Gabor小波的多方向、多尺度性质,将其分成13个通道。利用各个通道对表情识别率贡献不同的特点,提出了一种最优通道模糊积分融合的人脸表情识别算法。首先,提出最优通道选取的三条原则,根据这三条原则选取出3个最优通道;然后,提取表情图像经过最优通道的Gabor特征,并进行降维处理;最后,将每个最优通道作为一个分类器,用基于模糊积分的多分类器联合的方法对它们进行融合处理。在JAFFE库上进行测试取得了94.41%的识别率,验证了该算法的有效性。

According to its characteristics of multi-direction and multi-scale, Gabor wavelet is divided into 13 channels. Due to different contributions of different channels to the recognition rate, a fuzzy integral fusion approach for facial expression recognition is proposed based on optimal channels. Firstly, three optimal channels are selected according to three proposed principles. And then Gabor features of facial expressional images through those optimal channels are extracted with the dimensions reduction. Finally, each optimal channel is used as a classifier and three classifiers are fused based on multi-classifier combination with fuzzy integral. With the results on JAFFE database, it is found that the recognition rate of the proposed algorithm is 94.41 %, which verifies the effectiveness of the proposed algorithm.